5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
LIZARRALDE-Tensions and complexities in creating a sustainable and resilient ...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
VIGURIA-Automatic and on-board forest fire monitoring system-ID1256-IDRC2014_bGlobal Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
LIZARRALDE-Tensions and complexities in creating a sustainable and resilient ...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
VIGURIA-Automatic and on-board forest fire monitoring system-ID1256-IDRC2014_bGlobal Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
KURADA-Methodology of technological disasters risk determination-ID1057-IDRC2...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
MENG-Risk differentiation for critical infrastructure protection-ID1504-IDRC2...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
KornakovaMarchAmethodforlearningacrossdifferentdisastercasesexampleoftheurban...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
TYUBEE-Assessment of vulnerability of rural households to climate hazards-ID1...Global Risk Forum GRFDavos
This study assessed the vulnerability of rural households to climate hazards in mountainous areas of Kwande Local Government Area, Benue State, Nigeria. The objectives were to investigate major climate hazards, analyze variation in household vulnerability levels, and assess adaptation strategies. Regarding climate hazards, erosion and flooding were most frequent while landslides caused the most damage. A vulnerability assessment of 50 households found that adaptive capacity factors like healthcare and roads were most vulnerable. Household vulnerability scores averaged 5.3 out of 7, indicating significant vulnerability. Common adaptation strategies included changing agriculture, relocating, and changing livelihoods.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
The document discusses an integrated approach to risk and crisis management for terrorist attacks on public transportation networks. It presents a methodology developed by Cologne University of Applied Sciences (CUAS) to combine risk management and crisis management processes. The CUAS approach includes developing a crisis management process model, identifying interfaces between risk and crisis management, and assessing interdependencies. Simulation, tabletop, and crisis management exercises are used to collect data and validate the integrated approach. The goal is to enable transportation providers to more effectively protect their systems with less effort through an integrated risk and crisis management system.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Fragility analysis of open ground storey rc building designed using various m...eSAT Journals
Abstract The vulnerability of an element is defined as the probability that the said element will sustain a specified degree of structural damage given a certain level of ground motion severity. Significantly low stiffness and strength in any storeys compared to adjacent storeys is generally referred to as soft ground storey. As the columns of this Open ground storey are weakest element, ground storey is most vulnerable. Open ground storey framed buildings are generally analyzed in practice ignoring infill wall stiffness (linear bare frame analysis). Design codes impose a multiplication factor on the design forces in the columns of ground storey. The present study attempts to estimate and compare performance of open ground storey building designed with three different multiplication factors given by Indian code and Israel code. Thus fragility curves are derived using nonlinear dynamic time history analysis carried on a (G+9) OGS building by using method suggested by Cornell. Probabilistic seismic demand models are developed by using power law model. Results show that performance of upper storeys while applying multiplication factor only to the ground storey needs to be checked. The first storey is more vulnerable than the ground storey except for Israel code. Keywords: Open ground storey, multiplication factors, fragility, performance levels, PSDM Model
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
KURADA-Methodology of technological disasters risk determination-ID1057-IDRC2...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
MENG-Risk differentiation for critical infrastructure protection-ID1504-IDRC2...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
KornakovaMarchAmethodforlearningacrossdifferentdisastercasesexampleoftheurban...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
TYUBEE-Assessment of vulnerability of rural households to climate hazards-ID1...Global Risk Forum GRFDavos
This study assessed the vulnerability of rural households to climate hazards in mountainous areas of Kwande Local Government Area, Benue State, Nigeria. The objectives were to investigate major climate hazards, analyze variation in household vulnerability levels, and assess adaptation strategies. Regarding climate hazards, erosion and flooding were most frequent while landslides caused the most damage. A vulnerability assessment of 50 households found that adaptive capacity factors like healthcare and roads were most vulnerable. Household vulnerability scores averaged 5.3 out of 7, indicating significant vulnerability. Common adaptation strategies included changing agriculture, relocating, and changing livelihoods.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
The document discusses an integrated approach to risk and crisis management for terrorist attacks on public transportation networks. It presents a methodology developed by Cologne University of Applied Sciences (CUAS) to combine risk management and crisis management processes. The CUAS approach includes developing a crisis management process model, identifying interfaces between risk and crisis management, and assessing interdependencies. Simulation, tabletop, and crisis management exercises are used to collect data and validate the integrated approach. The goal is to enable transportation providers to more effectively protect their systems with less effort through an integrated risk and crisis management system.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Fragility analysis of open ground storey rc building designed using various m...eSAT Journals
Abstract The vulnerability of an element is defined as the probability that the said element will sustain a specified degree of structural damage given a certain level of ground motion severity. Significantly low stiffness and strength in any storeys compared to adjacent storeys is generally referred to as soft ground storey. As the columns of this Open ground storey are weakest element, ground storey is most vulnerable. Open ground storey framed buildings are generally analyzed in practice ignoring infill wall stiffness (linear bare frame analysis). Design codes impose a multiplication factor on the design forces in the columns of ground storey. The present study attempts to estimate and compare performance of open ground storey building designed with three different multiplication factors given by Indian code and Israel code. Thus fragility curves are derived using nonlinear dynamic time history analysis carried on a (G+9) OGS building by using method suggested by Cornell. Probabilistic seismic demand models are developed by using power law model. Results show that performance of upper storeys while applying multiplication factor only to the ground storey needs to be checked. The first storey is more vulnerable than the ground storey except for Israel code. Keywords: Open ground storey, multiplication factors, fragility, performance levels, PSDM Model
This document discusses using ODEs (ordinary differential equations) in MATLAB. It begins by introducing initial value problems for ODEs and numerical solutions. It then describes Euler's method for solving first-order ODEs and provides an example of using it to model bacterial growth. Built-in ODE solvers like ode23 and ode45 are introduced. The document also covers solving second-order ODEs by converting them to a system of first-order equations, solving systems of ODEs, stiffness, and passing additional parameters to ODE functions.
The document discusses several key concepts related to the Fourier transform:
1) It introduces the Dirac delta function and explains how it relates to the Fourier transform of exponential and cosine functions.
2) It describes several theorems regarding how the Fourier transform is affected by scaling, shifting, summing and differentiating functions.
3) It explains that both the intensity and phase of a time domain function, and the spectral intensity and phase in the frequency domain, are needed to fully characterize the function and its Fourier transform.
This document provides an overview of hazard maps and fragility maps. It discusses how fragility maps are constructed using fragility curves, which relate the probability of different damage states to the demand placed on a structure. Fragility curves are developed for different building types using numerical modeling and accounting for uncertainty. Shake maps are also discussed, which map ground shaking from earthquakes using ground motion prediction equations and sensor data. A case study on developing fragility maps for building types in Honduras is presented to demonstrate the process.
This document summarizes key points from lectures on Fourier analysis and frequency response functions for single degree of freedom oscillators. It recaps concepts like natural frequency, damping ratio, and dynamic amplification factor. It introduces Fourier series as a way to decompose periodic signals into harmonic components. The Fourier transform is presented as a way to study the frequency content of both periodic and non-periodic signals. Examples are given to illustrate the effects of varying parameters in the time and frequency domains.
Multi-objective optimization for the probabilistic seismic performance based design of an example moment frame steel structure is presented. Direct economic and social losses associated with seismic events, which are of interest in the current recommended frameworks for the performance based design of structures, are considered in the optimization problem defined. Three optimization objectives are selected: the initial construction cost, modeled as the weight of the structural system; expected annual economic loss associated with damage resulting from seismic hazard; and expected annual social loss resulting from seismic hazard induced damage. Hazus recommended procedures are applied in the economic and social loss calculations which include the fragility functions used in the damage analyses and injury event models implemented in the social loss calculations. The multiobjective optimization method uses a non-dominated sorting genetic algorithm strategy. The optimization results for the multiple objectives are presented and discussed in the form of Pareto fronts. Engineering demand parameters implemented for the seismic loss analysis are inter-story drifts and peak floor accelerations and are obtained using inelastic time history analysis for the ground motions associated with various seismic hazard levels. To illustrate the design procedure, loss parameters are calculated for an example steel structure located in Los Angeles, CA.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Investments in Italy to improve the resilience of infrastructural systems for...OECD Governance
Investing in infrastructure: Costs, benefits and effectiveness of disaster risk reduction measures.
Presentation made by:
M. Dolce,
Director General - Italian Civil Protection Department, Rome
Professor of Structural Engineering, University of Naples, Federico II
Exploration & Production onshore and offshore: technical challenges and their...ITE Oil&Gas
Presentation at TUROGE 2014 (Turkish International Oil and Gas Conference) on Safety of Onshore and Offshore Oil & Gas Operations.
By Giovanni Uguccioni - Oil & Gas Sector Development Manager at D’Appolonia SpA, Italy
This document discusses catastrophe risk modeling and quantification of economic impacts from extreme climate risks. It provides an overview of how catastrophe risk models are built and used to support risk management decisions for the insurance industry. The modeling approach involves identifying a study region, characterizing hazards, defining asset exposure, modeling damage, and estimating losses. Catastrophe risk models serve various segments of the insurance industry as well as other private and public entities involved in risk assessment and financing.
Panel I: "International Disaster and Risk Reduction, Sustainability and Resiliency"
Wolfgang Kroeger, Professor, ETH Risk Center, ETH Zurich, Zurich, Switzerland
New Models and New Technologies for an Integrated Risk Management in Complex ...Community Protection Forum
- The document discusses new models and technologies for integrated risk management in complex environments. It provides context on why the Workers Compensation Authority is involved in risk conferences and the objectives of INAIL beyond just compensation.
- It then discusses how concepts of risk and safety have evolved from a traditional safety-based approach to an integrated risk management approach in regulations and standards. Examples are provided of major accidents that revealed weaknesses in the prior safety-based approach.
- The presentation emphasizes that science and increasing knowledge can help make communities and workplaces safer by enabling more informed risk-based decisions, knowledge sharing, and learning from experiences including accidents and near misses. Ongoing research is important to address uncertainties.
Forest fires become the most frequent large-scale natural disasters, the protection
from which is a complex, labor-consuming and expensive process. The extent of the
damage from fires in Russia amounts to 20-110 billion rubles annually. Forest fires
that raged in October 2017, Northern California, caused damage of $9 billion dollars.
Today the most effective and safe means of firefighting are fire-prevention robotic
systems.
Research-and-production Enterprise «Tenzosensor» with the support of the
Russian Federation Ministry of education and science and in collaboration with FBI
«Avialesokhrana» develops the multiagent robotic system for forest firefighting.
The scientific objectives of the study are: justification of the composition of the
light multiagent robotic system for forest firefighting; justification of the structure of
the multiagent remote control system; justification of the unified control interface
composition based on polijoysticks.
The set tasks were solved by the methods of experimental modeling and theoretical
analysis of the obtained results.
As a result of the research the following results were received: the new
composition of multiagent robotic system for forest firefighting was
developed including; the structure of hierarchical multiagent remote control system
was developed; the unified polijoysticks-based interface for the control of the
multiagent robotic system elements.
It is expected that by its performance and efficiency the developed robotic system
will be able to replace a brigade of firemen of 40-60 people
ISACA SLOVENIA CHAPTER October 2016 - LubianaLuca Moroni ✔✔
Talk Luca Moroni - Via Virtuosa
Cyber security awareness of critical infrastructures in N/E of Italy: scenarios and guidelines for self-assesementOzaveščenost o varnosti spleta in kritične infrastrukture v severni Italiji: Scenariji in smernice kako opraviti samooceno
Dsd int 2014 - open mi symposium -cipr-net and openmi, erick rome, fraunhoferDeltares
CIPRNet is a European research network funded by the EU to improve critical infrastructure preparedness and resilience. The network aims to deploy new capabilities like advanced decision support and modeling/simulation/analysis of infrastructure interdependencies to support emergency managers. CIPRNet also focuses on community building and establishing a Virtual Centre of Competence & Expertise in critical infrastructure protection. This meeting with OpenMI focuses on collaborating to enhance modeling and simulation approaches for analyzing complex critical infrastructure scenarios.
This document discusses sociotechnical systems resilience and its impacts. It defines resilience as a system's ability to cope with unpredictable events, adjust to disturbances, and adapt and learn rules. Resilience is influenced by factors like crew training, procedures, and human-system interfaces. Incorporating resilience requires changes to systems engineering processes, models, architecture, and operations to account for human and contextual factors, support adaptation and learning from experiences, and enable flexible, evolvable systems.
Case study has been carried out on safety of industrial plants. .Various research papers are studied . Safety of the plants are important factor in mechanical engineering .
This 3 sentence summary provides the key details about the IRMA project:
The IRMA project aims to build an integrated risk management platform in Africa to help address disaster risk reduction across all phases from risk assessment to recovery. The platform will integrate various information sources and provide tools and services to stakeholders in natural disaster management. It seeks to demonstrate the capacity of standardized and interoperable ICT solutions to effectively mitigate disaster risk through operational scenarios assessing applications for bushfire, flood, desertification and urban risks management.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
This document discusses disaster risk management and modeling. It describes the need for mainstreaming pre-hazard risk management due to increasing losses from natural disasters. It then outlines a hazard risk management framework including risk assessment, mitigation investments, emergency preparedness, and institutional capacity building. Examples are provided of vulnerability mapping and modeling projects conducted in India and Romania to estimate disaster losses. A case study describes developing a disaster risk profile for Maldives using hazard and vulnerability assessments to create risk maps and inform development planning.
Seismic Fragility of Equipment and Support Structure in a Unit of an Oil Comp...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
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Global alliance of disaster research institutes (GADRI) discussion session, A...Global Risk Forum GRFDavos
Global Alliance of Disaster Research Institutes (GADRI) aims to reduce disaster risk and increase resilience through interdisciplinary research. GADRI brings together institutions to support research efforts through cooperation instead of competition. It also guides new researchers and maintains institutional memory to build upon past work. Some challenges GADRI may face include coordinating a global alliance. Solutions include facilitating cooperative work between members and guiding the expanding field of disaster reduction research.
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The document discusses concepts related to ensuring a safe, secure, and sustainable energy supply. It introduces the concepts of risk assessment, resilience management, security of supply, sustainability, and multi-criteria decision analysis. It then presents a case study from the EU SECURE project that used these concepts to evaluate policy scenarios according to various environmental, economic, social, and security indicators. The study found that global climate policy scenarios generally performed best, though they were vulnerable to certain shocks like nuclear accidents or carbon capture failures. Overall policies that reduced fossil fuel use and led to greater diversification of energy sources and imports improved sustainability and security.
Making Hard Choices An Analysis of Settlement Choices and Willingness to Retu...Global Risk Forum GRFDavos
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The Relocation Challenges in Coastal Urban Centers Options and Limitations, A...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
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The document summarizes the Global Alliance of Disaster Research Institutes (GADRI). GADRI is a global network of over 100 disaster research institutes that aims to enhance disaster risk reduction through knowledge sharing. It holds symposia, workshops, and other events on topics like flash floods, earthquakes, and geohazards. Notable upcoming events include the Third Global Summit of Research Institutes for Disaster Risk Reduction in 2017. GADRI's goals are to establish collaborative research initiatives, form international working groups, and disseminate findings to influence disaster policy.
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FORTE-Seismic risk assessment of industrial plants a case study-ID1277-IDRC2014_b
1. Please add your
Seismic Risk Assessment of Industrial
Plants: A Case Study from the Emilia
5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
2012 Earthquake Sequence
Marcello Forte, Davide Spanò, Fabio Petruzzelli,
AXA MATRIX Risk Consultants, Milan, Italy
logo here
2. Motivation of the study
5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
• Recent seismic events affecting industrialized countries (Japan, 2011; Emilia, 2012) readily showed the
importance of having an efficient, transparent and proactive management of the seismic risk.
• Traditional seismic risk assessment heavily rely on qualitative risk estimates, based on macroseismic
intensity and/or expert judgment. However, an essential step of an aware risk management and decision
making process is a sound quantitative risk assessment. This requires specific, rapid and user-friendly
tools, able to capture the peculiarities of the structure under investigation and the differences
between available models for modelling risk.
• Development of instruments for a rapid and user-friendly
probabilistic seismic risk assessment:
“FRAME@Risk” – Fragility-based rapid seismic Risk
Assessment Method” v.1.0 software
• Test the procedures on real cases
3. 5th International Disaster and Risk Conference IDRC 2014
Under human control
Exposure
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
From a qualitative to a quantitative (probabilistic)
seismic risk assessment
Quantitative approaches to seismic risk encompass individual quantification of the three component of seismic risk,
namely the seismic hazard (seismicity of the site); the vulnerability (building structural response); and the exposure
(building occupancy and contents).
Risk = H x V x E
Hazard
Vulnerability
4. Seismic risk is defined as the the probability or likelihood of exceeding a pre-defined level of loss due to earthquakes to a
given element at risk, over a specified period of time.
Failure Probability
Fragility Curves
(probability of exceeding some damage state)
Structural Engineering
Consequence function
(or damage-to-loss function)
stakeholders
Moderate
5th International Disaster and Risk Conference IDRC 2014
Hazard Curve
Seismologists
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
Expected loss
www.grforum.org
Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Seismic Risk Assessment
Exceedance probability
Intensity Measure (IM)
Hazard
Exceedance probability
Intensity Measure (IM)
Fragility
Expected Loss given a
damage state (“failure”)
Exposure
퐸 퐿 = 퐸 퐿|푓 ∙ 푃푓
퐸 퐿|푓
Slight
Collapse
Hazard
Curve
Fragility
Curve Pf = failure probability
(proportional to the
overlapping area)
5. Comparison&conversion tool Loss module
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
The FRAME@Risk software
the ensemble of FRAME@Risk
modules:
(i) allows performing a rapid,
user-friendly and worldwide
applicable evaluation of
structure-specific seismic
losses;
(ii) provides an inventory of
existing fragility functions
that can be managed and
expanded (to date, about
600 fragility functions);
(iii) allows the comparison and
homogenization of fragility
curves;
(iv) provides instruments for the
identification of the most
suitable fragility curves,
among those available, to
describe the seismic
performance of a structure.
The FRAME@Risk software tool
FRAME main module
Manager tool
MAIN FUNCTIONS:
• define a new fragility curve;
according to taxonomy;
• collapse and expand taxonomy;
• open/modify existing curves.
MAIN FUNCTIONS:
• compare fragility curves;
• convert IMs;
•manipulate limit states;
• compute statistics.
MAIN FUNCTIONS:
• choose damage-to-loss
functions;
• compute losses due to PD
and BI.
Fragility filter tool
MAIN FUNCTION:
• filter fragilities according to
the selected taxonomy.
• Allows the input of the data
required for the assessment:
− site-specific hazard,
− fragility curves suitable for
the case under
consideration,
− damage-to-loss function)
• Provides the output:
− failure probabilities
− expected losses
6. • The affected area is characterized by an high cultural and historical heritage and it is one of the most densely
industrialized Italian centers (the 2% of the Italian GDP is produced by activities in the stricken area)
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
The Emilia 2012 earthquake sequence
• M 5.9 earthquake on 20th May 2012 - 4:03 am UTC. Epicenter: close to Finale Emilia; depth: 6.3 Km.
• M 5.8 earthquake on 29th May - 9:00 am UTC. Epicenter: Medolla (18 km S-W far from the 1st event); depth: 10 Km.
The seismic sequence covered a large area extending in the E-W
direction for a length of nearly 40 km, between the localities of
Mirandola and Ferrara [INGV, 2012]
• Consequences:
− 27 casualties
− about 400 injured and 15,000 homeless
− 13.2 billion Euros of property damage and BI (Italian
Department for Civil Protection);
− 1.3 billion Euros of Insured Losses
(10% of Total Losses; in L’Aquila 2009 about the 2%)
• Causes:
− enforcement of seismic provisions in the affected
area only in 2009 (2003 for strategic buildings).
− Soft alluvial subsoil in the area caused significant
ground shaking amplification and, in some cases,
soil liquefaction.
7. 11 7 8
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Building characteristics
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4 5
6
9
10 12
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
The Case Study Plant
1
2
3
• fragility functions specifically
computed for Italian precast
buildings with different details in
terms of joint, reinforcement,
structural regularities, and
cladding characteristics.
• The consequence function was
chosen on the basis of the
content vulnerability class
• Plant dedicated to the production of medical devices;
• Total property value = about 100 million Euros (buildings = 27 mln; machineries=47 mil; stock=28 mln);
• 12 buildings, built from 1966 to 2011;
• Maximum horizontal acceleration (PGA) registered at the site = 0.3 g [INGV, 2012]
• After the earthquakes the plant suffered about 5.5 million euros o PD and about 2 months of downtime
• AXA MATRIX knowledge forms for industrial buildings
• Design documents
o geometrical characteristics (e.g. number of floors, height,
plan and elevation dimensions)
o mechanical characteristics (e.g. material, load resisting
system, detailing, irregularities, etc.)
o detailed description of the observed damage
Building characteristics
Building and content/equipment vulnerability
(from FRAME@Risk inventory)
Building exposed value
[% of the total plant value]
name material
design
year
fragility curve
vulnera-bility
class
Building
Machineries
&Equipment
Stock
Bld.1-Offices Cast in pl. r.c. 1990 AXA_CLASS_RC-MRF-MR-NC Medium 7,58% 0,6% 0,00%
Bld.2-Production Precast r.c. 1983 BologniniEtAl2008_FW10_type4//ND-IRR Fragile 12,6% 45,5% 2,9%
Bld.3-Production Precast r.c. 1983 BologniniEtAl2008_FW4_type1//D-IRR Robust 5,3% 19,3% 1,2%
Bld.4-Production Precast r.c. 1990 BologniniEtAl2008_FW4_type1//D-IRR Medium 5,0% 17,9% 1,1%
Bld.5-Warehouse Precast r.c. 2011 BologniniEtAl2008_FW4_type4//D-REG Robust 12,7% 0,6% 8,7%
Bld.6-Production Precast r.c. 1977 BologniniEtAl2008_FW10_type3//ND-IRR Fragile 15,1% 5,2% 7,2%
Bld.7-Production Precast r.c. 2002 BologniniEtAl2008_FW10_type1//D-IRR Fragile 9,7% 3,3% 3,5%
Bld.8-Warehouse Precast r.c. 1982 BologniniEtAl2008_FW10_type3//ND-REG Robust 6,7% 0,3% 9,5%
Bld.9-Warehouse Precast r.c. 2003 BologniniEtAl2008_FW4_type3//D-REG Robust 15,3% 0,7% 42,1%
Bld.10-Warehs. Precast r.c. 1993 BologniniEtAl2008_FW4_type2//D-REG Robust 3,3% 0,7% 18,5%
Bld.11-Product. Cast in pl. r.c. 1966 AXA_CLASS_RC-MRF-LR-NC Medium 2,6% 5,7% 0,9%
Bld.12-Warehs. Precast r.c.
1972-
1981
BologniniEtAl2008_FW10_type3//ND-REG Robust 4,2% 0,2% 4,5%
Building and content/equipment vulnerability
(from FRAME@Risk inventory)
Building exposed value
[% of the total plant value]
fragility curve
vulnera-bility
class
Building
Machineries
&Equipment
Stock
AXA_CLASS_RC-MRF-MR-NC Medium 7,58% 0,6% 0,00%
BologniniEtAl2008_FW10_type4//ND-IRR Fragile 12,6% 45,5% 2,9%
BologniniEtAl2008_FW4_type1//D-IRR Robust 5,3% 19,3% 1,2%
BologniniEtAl2008_FW4_type1//D-IRR Medium 5,0% 17,9% 1,1%
BologniniEtAl2008_FW4_type4//D-REG Robust 12,7% 0,6% 8,7%
BologniniEtAl2008_FW10_type3//ND-IRR Fragile 15,1% 5,2% 7,2%
BologniniEtAl2008_FW10_type1//D-IRR Fragile 9,7% 3,3% 3,5%
BologniniEtAl2008_FW10_type3//ND-REG Robust 6,7% 0,3% 9,5%
BologniniEtAl2008_FW4_type3//D-REG Robust 15,3% 0,7% 42,1%
BologniniEtAl2008_FW4_type2//D-REG Robust 3,3% 0,7% 18,5%
AXA_CLASS_RC-MRF-LR-NC Medium 2,6% 5,7% 0,9%
BologniniEtAl2008_FW10_type3//ND-REG Robust 4,2% 0,2% 4,5%
Building and content/equipment vulnerability
(from FRAME@Risk inventory)
Building exposed value
[% of the total plant value]
name material
design
year
fragility curve
vulnera-bility
class
Building
Machineries
&Equipment
Stock
Bld.1-Offices Cast in pl. r.c. 1990 AXA_CLASS_RC-MRF-MR-NC Medium 7,58% 0,6% 0,00%
Bld.2-Production Precast r.c. 1983 BologniniEtAl2008_FW10_type4//ND-IRR Fragile 12,6% 45,5% 2,9%
Bld.3-Production Precast r.c. 1983 BologniniEtAl2008_FW4_type1//D-IRR Robust 5,3% 19,3% 1,2%
Bld.4-Production Precast r.c. 1990 BologniniEtAl2008_FW4_type1//D-IRR Medium 5,0% 17,9% 1,1%
Bld.5-Warehouse Precast r.c. 2011 BologniniEtAl2008_FW4_type4//D-REG Robust 12,7% 0,6% 8,7%
Bld.6-Production Precast r.c. 1977 BologniniEtAl2008_FW10_type3//ND-IRR Fragile 15,1% 5,2% 7,2%
Bld.7-Production Precast r.c. 2002 BologniniEtAl2008_FW10_type1//D-IRR Fragile 9,7% 3,3% 3,5%
Bld.8-Warehouse Precast r.c. 1982 BologniniEtAl2008_FW10_type3//ND-REG Robust 6,7% 0,3% 9,5%
Bld.9-Warehouse Precast r.c. 2003 BologniniEtAl2008_FW4_type3//D-REG Robust 15,3% 0,7% 42,1%
Bld.10-Warehs. Precast r.c. 1993 BologniniEtAl2008_FW4_type2//D-REG Robust 3,3% 0,7% 18,5%
Bld.11-Product. Cast in pl. r.c. 1966 AXA_CLASS_RC-MRF-LR-NC Medium 2,6% 5,7% 0,9%
Bld.12-Warehs. Precast r.c.
1972-
1981
BologniniEtAl2008_FW10_type3//ND-REG Robust 4,2% 0,2% 4,5%
8. Results of the analysis (1/3)
Comparison of the estimated physical damage (FRAME@Risk software) to the observed one
Large part of the production took place in Bld. 2 and Bld.6, that were also those which suffered the major structural
damages
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‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Building characteristics
Building and content/equipment vulnerability
(from FRAME@Risk inventory)
Building exposed value
[% of the total plant value]
name material
design
year
fragility curve
vulnera-bility
class
Building
Machineries
&Equipment
Stock
Bld.1-Offices Cast in pl. r.c. 1990 AXA_CLASS_RC-MRF-MR-NC Medium 7,58% 0,6% 0,00%
Bld.2-Production Precast r.c. 1983 BologniniEtAl2008_FW10_type4//ND-IRR Fragile 12,6% 45,5% 2,9%
Bld.3-Production Precast r.c. 1983 BologniniEtAl2008_FW4_type1//D-IRR Robust 5,3% 19,3% 1,2%
Bld.4-Production Precast r.c. 1990 BologniniEtAl2008_FW4_type1//D-IRR Medium 5,0% 17,9% 1,1%
Bld.5-Warehouse Precast r.c. 2011 BologniniEtAl2008_FW4_type4//D-REG Robust 12,7% 0,6% 8,7%
Bld.6-Production Precast r.c. 1977 BologniniEtAl2008_FW10_type3//ND-IRR Fragile 15,1% 5,2% 7,2%
Bld.7-Production Precast r.c. 2002 BologniniEtAl2008_FW10_type1//D-IRR Fragile 9,7% 3,3% 3,5%
Bld.8-Warehouse Precast r.c. 1982 BologniniEtAl2008_FW10_type3//ND-REG Robust 6,7% 0,3% 9,5%
Bld.9-Warehouse Precast r.c. 2003 BologniniEtAl2008_FW4_type3//D-REG Robust 15,3% 0,7% 42,1%
Bld.10-Warehs. Precast r.c. 1993 BologniniEtAl2008_FW4_type2//D-REG Robust 3,3% 0,7% 18,5%
Bld.11-Product. Cast in pl. r.c. 1966 AXA_CLASS_RC-MRF-LR-NC Medium 2,6% 5,7% 0,9%
Bld.12-Warehs. Precast r.c.
1972-
1981
BologniniEtAl2008_FW10_type3//ND-REG Robust 4,2% 0,2% 4,5%
9. Results of the analysis (1/3)
Comparison of the estimated physical damage (FRAME@Risk software) to the observed one
Building 9 was subject to slight damage and minor to moderate loss of content
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Building characteristics
Building and content/equipment vulnerability
(from FRAME@Risk inventory)
Building exposed value
[% of the total plant value]
name material
design
year
fragility curve
vulnera-bility
class
Building
Machineries
&Equipment
Stock
Bld.1-Offices Cast in pl. r.c. 1990 AXA_CLASS_RC-MRF-MR-NC Medium 7,58% 0,6% 0,00%
Bld.2-Production Precast r.c. 1983 BologniniEtAl2008_FW10_type4//ND-IRR Fragile 12,6% 45,5% 2,9%
Bld.3-Production Precast r.c. 1983 BologniniEtAl2008_FW4_type1//D-IRR Robust 5,3% 19,3% 1,2%
Bld.4-Production Precast r.c. 1990 BologniniEtAl2008_FW4_type1//D-IRR Medium 5,0% 17,9% 1,1%
Bld.5-Warehouse Precast r.c. 2011 BologniniEtAl2008_FW4_type4//D-REG Robust 12,7% 0,6% 8,7%
Bld.6-Production Precast r.c. 1977 BologniniEtAl2008_FW10_type3//ND-IRR Fragile 15,1% 5,2% 7,2%
Bld.7-Production Precast r.c. 2002 BologniniEtAl2008_FW10_type1//D-IRR Fragile 9,7% 3,3% 3,5%
Bld.8-Warehouse Precast r.c. 1982 BologniniEtAl2008_FW10_type3//ND-REG Robust 6,7% 0,3% 9,5%
Bld.9-Warehouse Precast r.c. 2003 BologniniEtAl2008_FW4_type3//D-REG Robust 15,3% 0,7% 42,1%
Bld.10-Warehs. Precast r.c. 1993 BologniniEtAl2008_FW4_type2//D-REG Robust 3,3% 0,7% 18,5%
Bld.11-Product. Cast in pl. r.c. 1966 AXA_CLASS_RC-MRF-LR-NC Medium 2,6% 5,7% 0,9%
Bld.12-Warehs. Precast r.c.
1972-
1981
BologniniEtAl2008_FW10_type3//ND-REG Robust 4,2% 0,2% 4,5%
10. Comparison of the estimated physical damage (FRAME@Risk software) to the observed one
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20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Results of the analysis (2/3)
Distribution of estimated losses inside the plant (normalized with respect to the total value of the component at risk)
0%
Building loss / total value [%]
Building
Machineries & Equipment
Stock
The large part of the stock is located in Bld.9 and Bld. 5, the good
structural characteristics of which limit the extent of the loss
Bld.2 and Bld.6 are those for which the largest
damage to building is observed
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100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Results of the analysis (3/3)
Comparison of estimated losses with the adjusted ones
• The comparison between FRAME@Risk estimates and the real losses is performed in terms of adjusted losses, rather
than claims. The comparison is done for building component only.
0%
Building loss / building value [%]
Expected Loss (FRAME@Risk estimate)
Adjusted Loss (after claim) Although a comparison of the expected losses obtained through a probabilistic approach with the losses deriving from
a single real event is hardly feasible, as a general result the total loss associated to the buildings is:
Adjusted = 5.5 million Euros 20% of the total building value
Estimated (FRAME@Risk) = 6.5 million Euros 24% of the total building value
- good coherency between estimated and adjusted losses was obtained,
- Losses are overestimated when structures experienced minor to null damage (e.g., Bld. 9)
- Conversely, in case of collapse (e.g. Bld.10 and Bld.2)
12. • Good coherency between the expected losses estimated by the procedure and the real losses was observed, with
a tendency in overestimating the observed loss for a given scenario earthquake was observed, that is almost
intrinsic in a probabilistic approach and more pronounced for structures that have experienced minor damages.
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Conclusions
• A case study from the Emilia Earthquake 2012 has been presented, with the aim of comparing the direct loss
estimations performed throughout the FRAME@Risk software against the loss adjusted after the claim process
• The application of the FRAME@Risk software tool showed the capability of the software in guiding the association
of a specific fragility curve to a given structure, on the basis of the taxonomy collected on field, and in addressing
the major deficiencies among the buildings of the plant.
• In the case study, the most vulnerable buildings were also those most exposed, i.e. those where large part of the
production took place. This is believed to be a fundamental information useful to the stakeholder’s decision making,
allowing to relocate or undertake countermeasures to reduce the impacts of a potential earthquake event.
• Nevertheless, the success of this analysis is related to the knowledge level that has been possible to achieve about
the structures under investigation and the availability of fragility curves suitable for describing the seismic
behaviour of structures.
13. – main references –
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Seismic Risk Assessment of Industrial Plants: a Case Study from the Emilia 2012 Earthquake Sequence
Fabio Petruzzelli, PhD, Loss Prevention Engineer – AXA MATRIX Risk Consultants, Milan, Italy
Thanks for your kind attention
Bolognini D., Borzi B., Pinho R. (2008). Simplified Pushover-based Vulnerability Analysis of Traditional Italian RC precast structures.
Proceedings of the 14th World Conference on Earthquake Engineering, October 12-17, 2008 Bejing, China.
Cornell C. A. and Krawinkler H. (2000). Progress and challenges in seismic performance assessment. PEER News, April 3(2), Pacific Earthquake
Engineering Research Center, Berkeley, California, US.
Dowrick D.J. and Rhoades D.A. (1993). Damage costs for commercial and industrial property as a function of intensity in the 1987 Edgecumbe
earthquake. Earthquake Engineering and Structural Dynamics, 22, 869-884.
Parisi F., De Luca F., Petruzzelli F., De Risi R., Chioccarelli E., Iervolino I. (2012), Field inspection after the May 20th and 29th 2012 Emilia-
Romagna earthquakes, available at http://www.reluis.it.
Petruzzelli F (2013) Scale-dependent procedures for seismic risk assessment and management of industrial building portfolios Ph.D. Thesis in
Seismic Risk, XXV cycle, Università degli Studi di Napoli Federico II, Naples, Italy
Petruzzelli, F. and Iervolino, I. (2014). FRAME v.1.0: a rapid fragility-based seismic risk assessment tool. Proceedings of the 2ECEES, Second
European Conference on Earthquake Engineering and Seismology, Aug. 25-29, 2014, Istanbul, Turkey.
Fabio Petruzzelli, PhD
Loss Prevention Engineer
AXA MATRIX Risk Consultants, Milan, Italy
fabio.petruzzelli@axa-matrixrc.com
Editor's Notes
Quantitative seismic risk assessment, providing sound probabilistic estimates of potential earthquake impacts, is a key step of any meaningful and aware decision-making process.
Nine days later … causing additional damages, particularly to buildings already weakened by the 20th May shock
This was the first time since 1570 that an earthquake of this magnitude had hit this region
Large portion of the industrial building stock was made up of precast reinforced buildings, designed for wind actions or gravitational loads, due to enforcement of seismic provisions in the affected area only in 2009 (2003 for strategic buildings).
The damage observed was certainly exacerbated by the soft alluvial subsoil in the area, which caused significant ground shaking amplification and, in some cases, soil liquefaction.
The fragility database and the detailed taxonomy implemented in the tool allowed to employ fragility functions specifically computed for Italian precast buildings (e.g. Bolognini et al., 2008) with different details in terms of joint, reinforcement, structural regularities, and cladding characteristics.
Bld.2 and Bld.6 are those for which the largest damage to building is observed
The high vulnerability of Bld.2 is also the responsible for an expected loss to machineries&equipment of about 18% of the total value of equipment in the plant
Conversely, relatively low levels of losses are expected for buildings 5, 9 and 10, as a consequence of the recent design of their structures and of good structural characteristics and maintenance
Although a comparison of the expected losses obtained through a probabilistic approach with the losses deriving from a single real event is hardly feasible, as a general result it can be observed that FRAME@Risk provides, for the whole building portfolio, an average loss equal to the 25% of the total building value, with respect to an average adjusted loss of about the 20% (including debris removal for collapsed buildings).
The only cases in which an opposite trend (underestimated expected losses) emerged, were Bld.10 and Bld.2. The former was a warehouse dedicated to the storage of raw materials, with very low exposed values and losses (see Fig.5), which behaved, during the earthquakes, worse than it was reasonable to expect from its structural typology and characteristics. The latter, was the building in which the largest part of the production took place and the one that experienced the complete collapse. In this case, a unique damage state occurred (the complete collapse) and (almost) the total exposed value was actually lost. In a probabilistic approach this could have been taken into account through the choice of fragility curves providing an almost null probability of exceeding damage conditions different from the collapse. Nevertheless, this “almost deterministic” choice is hardly feasible in a predictive assessment of the seismic risk.
Moreover, due to the availability of adjusted losses for building damage only, the comparison was not performed for damages to machineries, equipment and contents, which may represent a further development of this study.
The assessment of expected losses due to the largest ground motion intensity felt at the site during the earthquake sequence was performed accounting for structural and non-structural damages, including those to machinery and equipment and stock contents.
This could be related to several factors:(i) the probabilistic nature of the assessment, (ii) the conventional definition of damage states, (iii) the adoption of a specific fragility curve and damage-to-loss function. While the first two points of the previous list are intrinsic in the approach, the last one is strictly related to the uncertainty in assessing structural and non-structural characteristics.
This could be related to several factors:(i) the probabilistic nature of the assessment, (ii) the conventional definition of damage states, (iii) the adoption of a specific fragility curve and damage-to-loss function. While the first two points of the previous list are intrinsic in the approach, the last one is strictly related to the uncertainty in assessing structural and non-structural characteristics.